{"id":20016,"date":"2025-06-02T17:56:17","date_gmt":"2025-06-02T15:56:17","guid":{"rendered":"https:\/\/2025.mining-report.de\/english\/?p=20016"},"modified":"2025-06-02T17:56:17","modified_gmt":"2025-06-02T15:56:17","slug":"ai-assistance-for-specialist-foundation-engineering-equipment-research-project-successfully-concluded","status":"publish","type":"post","link":"https:\/\/mining-report.de\/english\/blog\/ai-assistance-for-specialist-foundation-engineering-equipment-research-project-successfully-concluded\/","title":{"rendered":"AI assistance for specialist foundation engineering equipment: Research project successfully concluded"},"content":{"rendered":"

Operating large, mobile hydraulic construction equipment is a demanding task. Safe and efficient operation depends primarily on the operator\u2019s experience \u2013 expertise that can take years to acquire. Less experienced operators often reach their limits quickly. This is precisely where the recently concluded OPAI4DNCS research project, funded by the Bavarian Research Foundation (BFS), stepped in.<\/em><\/p>\n

Industry and science joining forces
\n<\/strong>For this project, BAUER Maschinen GmbH, HAWE Hydraulik SE and STW (Sensor- Technik Wiedemann GmbH) collaborated closely with the Chair of Automation and Information Systems as well as the Chair of Ergonomics at Munich Technical University. Over the course of three years, the project partners explored operator-centered assistance for mobile construction equipment used in specialist foundation engineering.<\/p>\n

Needs-based assistance from AI
\n<\/strong>The aim of this project was to develop adaptive, intelligent, and self-learning control systems based on multi-agent systems (MAS). The focus was on needs-based assistance of machine operators to enable safe operation even in borderline situations.<\/p>\n

\"\"<\/a>
Fig. 1. BAUER GB 50 hydraulic grab \u2013 the same grab type was used as a demonstrator in the research project. Photo: BAUER<\/figcaption><\/figure>\n

Bauer grab used as test vehicle
\n<\/strong>The technology was demonstrated using a hydraulic grab (Figure 1), typically used in the construction of diaphragm walls. The crucial factors were dampening vibrations and stabilizing the grab. Operating the grab is particularly challenging due to its swinging bucket. Using a soft sensor to measure the pendulum movements caused by pressure fluctuations on the hydraulic actuators, a real assistance system was development and successfully implemented in test campaigns.<\/p>\n

Human-AI collaboration
\n<\/strong>One central result of the project was the development of a shared-control platform that enables intuitive collaboration between human operators and artificial intelligence. A retrofitting solution was established that can extend existing control systems with intelligent functions, without requiring major changes to the machine\u2019s architecture. The assistance system offers three different control modes tailored to the operator\u2019s experience level. Combined with a multi-agent architecture, the system delivers flexible, context-sensitive assistance for complex control tasks \u2013 improving efficiency, safety and resource conservation on construction sites.<\/p>\n

Further information:
\nBAUER AG
\nwww.bauer.de<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"

Operating large, mobile hydraulic construction equipment is a demanding task. Safe and efficient operation depends primarily on the operator\u2019s experience \u2013 expertise that can take years to acquire. 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